Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

Optimized DWT Based Digital Image Watermarking and Extraction Using RNN-LSTM

The rapid growth of Internet and the fast emergence of multi-media applications over the past decades have led to new problems such as illegal copying, digital plagiarism, distribution and use of copyrighted digital data. Watermarking digital data for copyright protection is a current need of the community. For embedding watermarks, robust algorithms in die media will resolve copyright infringements. Therefore, to enhance the robustness, optimization techniques and deep neural network concepts are utilized. In this paper, the optimized Discrete Wavelet Transform (DWT) is utilized for embedding the watermark. The optimization algorithm is a combination of Simulated Annealing (SA) and Tunicate Swarm Algorithm (TSA). After performing the embedding process, the extraction is processed by deep neural network concept of Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM). From the extraction process, the original image is obtained by this RNN-LSTM method. The experimental set up is carried out in the MATLAB platform. The performance metrics of PSNR, NC and SSIM are determined and compared with existing optimization and machine learning approaches. The results are achieved under various attacks to show the robustness of the proposed work

Security of Electronic Patient Record using Imperceptible DCT-SVD based Audio Watermarking Technique

Abstract—A robust and highly imperceptible audio watermarkingtechnique is presented to secure the electronic patientrecord of Parkinson’s Disease (PD) affected patient. The proposedDCT-SVD based watermarking technique introduces minimalchanges in speech such that the accuracy in classification of PDaffected person’s speech and healthy person’s speech is retained.To achieve high imperceptibility the voiced part of the speech isconsidered for embedding the watermark. It is shown that theproposed watermarking technique is robust to common signalprocessing attacks. The practicability of the proposed technique istested: by creating an android application to record & watermarkthe speech signal. The classification of PD affected speech is doneusing Support Vector Machine (SVM) classifier in cloud server

Adaptive digital watermarking scheme based on support vector machines and optimized genetic algorithm

Digital watermarking is an effective solution to the problem of copyright protection, thus maintaining the security of digital products in the network. An improved scheme to increase the robustness of embedded information on the basis of discrete cosine transform (DCT) domain is proposed in this study. The embedding process consisted of two main procedures. Firstly, the embedding intensity with support vector machines (SVMs) was adaptively strengthened by training 1600 image blocks which are of different texture and luminance. Secondly, the embedding position with the optimized genetic algorithm (GA) was selected. To optimize GA, the best individual in the first place of each generation directly went into the next generation, and the best individual in the second position participated in the crossover and the mutation process. The transparency reaches 40.5 when GA’s generation number is 200. A case study was conducted on a 256 × 256 standard Lena image with the proposed method. After various attacks (such as cropping, JPEG compression, Gaussian low-pass filtering (3, 0. 5), histogram equalization, and contrast increasing (0.5, 0.6)) on the watermarked image, the extracted watermark was compared with the original one. Results demonstrate that the watermark can be effectively recovered after these attacks. Even though the algorithm is weak against rotation attacks, it provides high quality in imperceptibility and robustness and hence it is a successful candidate for implementing novel image watermarking scheme meeting real timelines

A Comprehensive Review on Digital Image Watermarking

The advent of the Internet led to the easy availability of digital data like images, audio, and video. Easy access to multimedia gives rise to the issues such as content authentication, security, copyright protection, and ownership identification. Here, we discuss the concept of digital image watermarking with a focus on the technique used in image watermark embedding and extraction of the watermark. The detailed classification along with the basic characteristics, namely visual imperceptibility, robustness, capacity, security of digital watermarking is also presented in this work. Further, we have also discussed the recent application areas of digital watermarking such as healthcare, remote education, electronic voting systems, and the military. The robustness is evaluated by examining the effect of image processing attacks on the signed content and the watermark recoverability. The authors believe that the comprehensive survey presented in this paper will help the new researchers to gather knowledge in this domain. Further, the comparative analysis can enkindle ideas to improve upon the already mentioned techniques